Local stability of T-S fuzzy systems is analyzed.
针对t - S型模糊系统进行局部稳定性分析。
Base on these concepts, the fuzzy systems are interpretable.
基于这些概念的模糊系统具有可理解性。
The stabilization of uncertain dynamical fuzzy systems is studied.
研究不确定动态模糊系统的稳定性问题。
This paper deals with filtering problems for a class of discrete-time fuzzy systems.
本论文考虑了一类离散模糊系统的滤波器设计问题。
The robust reliable control problem for a class of switched fuzzy systems is studied.
针对切换不确定模糊系统的模型研究了鲁棒可靠控制问题。
A new way combining neural networks and fuzzy systems is explored by means of this work.
此项工作为神经网络与模糊系统相结合探索了一条新的途径。
An approach to the technology with fuzzy systems, neural networks and genetic algorithms is given.
本文应用基于遗传算法的模糊神经网络方法，建立了科研项目立项评审的智能管理系统。
Fuzzy systems have demonstrated their ability for modeling or control in a huge number of applications.
模糊系统在实际系统的建模和控制中具有很多的应用。
In this paper, merging algorithms of fuzzy subsets and rules are proposed to deal with ts fuzzy systems.
本文针对TS模糊系统提出一种模糊子集和模糊规则的合并算法。
This paper discusses the problems of robust local stability and robust local stabilization of T-S fuzzy systems.
研究一类不确定t - S模糊系统的鲁棒局部稳定及鲁棒局部镇定问题。
Has been widely used in function optimization, training neural networks, fuzzy systems control, and other fields.
目前已广泛应用于函数优化，神经网络训练，模糊系统控制等领域。
Some properties of fuzzy relational matrix concerning with the stability of fuzzy systems are discussed in this paper.
讨论了模糊关系矩阵的若干与模糊系统稳定性相关的性质；
Taking complex industry process control as background, this research focuses on optimization problems of fuzzy systems.
本研究是以复杂生产过程为背景，在模糊系统优化领域开展的专项研究。
Moreover, a new fast learning method of fuzzy systems both based on genetic algorithms and gradient method is proposed.
实现了一种新的基于遗传算法和梯度下降方法的快速模糊系统学习算法。
In this dissertation, the problem of memory non-fragile control for a class of Takagi-Sugeno (T-S) fuzzy systems is studied.
本文从理论上研究了模糊系统的有记忆非易碎控制。
Radial Gaussian function networks based on fuzzy systems is applied to the state estimation of nonlinear time varying systems.
利用模糊系统的径向高斯函数网络对一类非线性时变系统的状态进行了估计。
The problem of adaptive tracking control for a class of T-S fuzzy systems with time-varying dead-zone is studied in this paper.
研究了一类带有时变死区的T-S模糊系统的自适应跟踪控制问题。
A sufficient condition is derived for the existence of passive state feedback controller for T-S fuzzy systems with time-delay.
针对时滞t - S模糊系统，给出了使得系统无源的状态反馈控制器存在的充分条件，与现有结果相比保守性更小。
So there has been a great deal of interest in applying model-free methods such as fuzzy systems for nonlinear function approximation.
因此依然有很多场合需要使用无模型方法—如用模糊系统进行非线性函数逼近等。
The problem of quadratic stability and controller design for T-S fuzzy systems is studied using the linear matrix inequality(LMI)methods.
应用LMI（线性矩阵不等式）方法，研究了T-S模糊系统二次稳定性及控制器设计问题。
But in this paper, this assumption is no longer a necessary condition, that is, we can control the T-S fuzzy systems with fast time-varying delays.
但是在本文不再需要这个假设，也就是说本文所采用的方法能处理快变时滞问题。
It gives a brief introduction to models and applications of genetic fuzzy systems, and analyses the directions and trends of research on fuzzy systems.
这里介绍了遗传模糊系统的各种模型和应用领域，分析了此领域的研究方向和趋势。
An inverted pendulum example of non-fragile controller design of uncertainty T-S fuzzy systems shows the feasibility and the effectiveness of the method.
通过对一级倒立摆的不确定模糊非脆弱控制器设计的实例，表明了设计方法的可行性和有效性。
Based on the approximation property of fuzzy systems, a nonlinear system can be expressed as the form of linear parametric model and a modelling error term.
根据模糊系统的逼近性质，非线性系统可以表示为线性参数化模型加上一建模误差项。
A robust control term was used to compensate the approximation error of fuzzy systems, which could reduce the effect on tracking accuracy caused by the error.
并用鲁棒控制项对模糊系统逼近误差进行补偿，减少了其对跟踪精度的影响。
The experimental results show that the proposed method can fuse multiple classifiers with low classification error rate based on comprehensible fuzzy systems.
实验结果表明，该方法能够用可理解性好的模糊系统实现低错误率的多分类器融合。
The experimental results show that the proposed method can fuse multiple classifiers with low classification error rate based on comprehensible fuzzy systems.
实验结果表明，该方法能够用可理解性好的模糊系统实现低错误率的多分类器融合。
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